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COVID-19 vaccine candidates and vaccine development platforms available worldwide

Journal of Pharmaceutical Analysis 2021年第6期11卷 675-682页

作者： Nilgun Duman zahraa alzaidi Busra Aynekin Duygu Taskin Busra Demirors Abdulbaki Yildirim Izem Olcay Sahin Faik Bilgili Eda Tahir Turanli Tommaso Beccari Matteo Bertelli Munis Dundar Department of Medical Genetics Dragos Hospital IstanbulBezmialem Vakif UniversityIstanbul34854Turkey Department of Biotechnology Faculty of Applied ScienceCukurova UniversityAdana01380Turkey Department of Medical Genetics Medical FacultyErciyes UniversityKayseri38030Turkey Department of Economics Faculty of Economics and Administrative SciencesErciyes UniversityKayseri38030Turkey Department of Molecular Biology and Genetics Faculty of ScienceAcibadem University34684IstanbulTurkey Department of Pharmaceutical Sciences University of PerugiaPerugia06123Italy MAGI'S LAB Trentino38068Italy

The pandemic caused by the worldwide spread of the coronavirus,which first appeared in 2019,has been named coronavirus disease 19(COVID-19).More than 4.5 million deaths have been recorded due to the pandemic caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),according to the World Health Organization.COVID-19 Dashboard in September 2021.Apart from the wildtype,other variations have been successfully transmitted early in the outbreak although they were not discovered until March 2020.Modifications in the SARS-CoV-2 genetic material,such as mutation and recombination,have the ability to modify the viral life span,along with transitivity,cellular tropism,and symptom severity.Several processes are involved in introducing novel vaccines to the population,including vaccine manufacturing,preclinical studies,Food and Drug Administration permission or certification,processing,and marketing.COVID-19 vaccine candidates have been developed by a number of public and private groups employing a variety of strategies,such as RNA,DNA,protein,and viral vectored vaccines.This comprehensive review,which included the most subsequent evidence on unique features of SARS-CoV-2 and the associated morbidity and mortality,was carried out using a systematic search of recent online databases in order to generate useful knowledge about the COVID-19 updated versions and their consequences on the disease symptoms and vaccine development.

关键词： COVID-19 vaccine Vaccine development platform Coronavirus outbreak SARS-CoV-2 variants Treatment

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In situ infiltration-precipitation processes in some rock systems

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地球化学学报(英文) 2023年第5期42卷 870-878页

作者： zahraa Ibrahim Rabih Sultan Department of Chemistry American University of BeirutBeirutLebanon

We carry out a chemical treatment(acidization or basification)of typical rock specimens in-situ,and characterize the emerging pattern resulting from the infil-tration-precipitation scenario.Galena and limestone sam-ples were treated with sulfuric acid,while pyrite was reacted with sodium hydroxide.Various infiltration tech-niques were employed,after selection of the most feasible method for each rock separately.The patterns of anglesite(PbSO_(4)),anhydrite(CaSO_(4))and goethite(FeOOH)depo-sition presented different alteration modes of the bare rock textures.Among the three deposited minerals,only the anhydrite(CaSO_(4))displayed a band stratification.The formation of a Liesegang pattern in the rock of highest porosity indicates a plausible correlation between the band formation and a minimum porosity requirement.A banded rock of compact texture could then be formed by a cementation mechanism,governing the long time evolution of the rock.

关键词： Liesegang Limestone Galena Pyrite Anglesite Goethite Reaction–diffusion Percolation Porosity Pattern formation

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Cranial differences in three-toed jerboas(Dipodinae,Dipodidae,Rodentia)according to recent taxonomic revisions

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Current Zoology 2023年第4期69卷 475-490页

作者： Bader H.Alhajeri zahraa Hasan Hasan Alhaddad Department of Biological Sciences Kuwait UniversitySafat13060Kuwait

Recent phylogenetic studies amended the taxonomy of three-toed jerboas(subfamily Dipodinae),including raising subspecies to full species.Here,we use geometric morphometrics to compare scaled-shape differences in dipodine crania while considering their revised taxonomy.We sampled Dipus deasyi,D.sagitta halli,D.s.sowerbyi,Jaculus blanfordi blanfordi,J.hirtipes,J.jaculus,J.loftusi,J.orientalis gerboa,J.o.mauritanicus,and Stylodipus andrewsi.Crania were not sexually dimorphic.Common allometry explained some of the shape variation,for example,reduced braincases in larger specimens.Most operational taxonomic unit pairs differed in both size and shape.Dipus and Stylodipus clustered together based on their cranial shape.Jaculus differed from the aforementioned genera by its larger tympanic bulla,broader braincase,larger infraorbital foramen,along with reduced molars and rostra.Jaculus orientalis differed from other Jaculus by its broader face versus reduced cranial vault.Jaculus blanfordi(subgenus Haltomys)resembles members of the subgenus Jaculus more than its consubgener(J.orientalis).Jaculus loftusi,previously considered a synonym of J.jaculus,clearly differed from the latter by its shorter rostrum,smaller infraorbital foramen,and more caudolaterally expanded tympanic bulla.Jaculus hirtipes,another recent synonym of J.jaculus,resembled J.blanfordi more in scaled cranial shape than it did J.jaculus.Dipus sagitta halli and D.s.sowerbyi were indistinguishable,but they clearly differed from D.deasyi(recently raised to full species)with the latter having a larger molar row,more inflated tympanic bulla,and shorter,slenderer rostrum.Ecological explanations for detected cranial shape differences are considered,including diet and habitat(particularly substrate).

关键词： crania Dipus deasyi Jaculus hirtipes Jaculus loftusi jerboa Stylodipus andrewsi

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Classification of Electroencephalogram Signals Using LSTM and SVM Based on Fast Walsh-Hadamard Transform

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Computers, Materials & Continua 2023年第6期75卷 5271-5286页

作者： Saeed Mohsen Sherif S.M.Ghoneim Mohammed S.alzaidi Abdullah Alzahrani Ashraf Mohamed Ali Hassan Electronics and Communications Engineering Department Al-Madinah Higher Institute for Engineering and TechnologyGiza12947Egypt Department of Artificial Intelligence Engineering Faculty of Computer Science and EngineeringKing Salman International University(KSIU)South Sinai46511Egypt Department of Electrical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Department of Electronics and Communications Engineering October High Institute for Engineering and Technology6th of October CityGiza12596Egypt

Classification of electroencephalogram(EEG)signals for humans can be achieved via artificial intelligence(AI)techniques.Especially,the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic regions.From this perspective,an automated AI technique with a digital processing method can be used to improve these signals.This paper proposes two classifiers:long short-term memory(LSTM)and support vector machine(SVM)for the classification of seizure and non-seizure EEG signals.These classifiers are applied to a public dataset,namely the University of Bonn,which consists of 2 classes–seizure and non-seizure.In addition,a fast Walsh-Hadamard Transform(FWHT)technique is implemented to analyze the EEG signals within the recurrence space of the brain.Thus,Hadamard coefficients of the EEG signals are obtained via the FWHT.Moreover,the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG recordings.Also,a k-fold cross-validation technique is applied to validate the performance of the proposed classifiers.The LSTM classifier provides the best performance,with a testing accuracy of 99.00%.The training and testing loss rates for the LSTM are 0.0029 and 0.0602,respectively,while the weighted average precision,recall,and F1-score for the LSTM are 99.00%.The results of the SVM classifier in terms of accuracy,sensitivity,and specificity reached 91%,93.52%,and 91.3%,respectively.The computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s,respectively.The results show that the LSTM classifier provides better performance than SVM in the classification of EEG signals.Eventually,the proposed classifiers provide high classification accuracy compared to previously published classifiers.

关键词： Electroencephalogram LSTM SVM fast Walsh-Hadamard transform seizure accuracy sensitivity specificity

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Efficient Data Compression of ECG Signal Based on Modified Discrete Cosine Transform

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Computers, Materials & Continua 2022年第6期71卷 4391-4408页

作者： Ashraf Mohamed Ali Hassan Mohammed S.alzaidi Sherif S.M.Ghoneim Waleed El Nahal Electronics and Communications Engineering Department Faculty of EngineeringSinai UniversityArishCO 45511Egypt Department of Electrical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Faculty of Technology and Education Suez UniversitySuez43527Egypt Electronics and Communications Engineering Department Faculty of EngineeringMSA UniversityCO 12585Egypt

This paper introduced an efficient compression technique that uses the compressive sensing(CS)method to obtain and recover sparse electrocardiography(ECG)signals.The recovery of the signal can be achieved by using sampling rates lower than the Nyquist frequency.A novel analysis was proposed in this paper.To apply CS on ECG signal,the first step is to generate a sparse signal,which can be obtained using Modified Discrete Cosine Transform(MDCT)on the given ECGsignal.This transformation is a promising key for other transformations used in this search domain and can be considered as the main contribution of this paper.A small number of wavelet components can describe the ECG signal as related work to obtain a sparse ECGsignal.Asensing technique for ECGsignal compression,which is a novel area of research,is proposed.ECG signals are introduced randomly between any successive beats of the heart.MIT-BIH database can be represented as the experimental database in this domain of research.TheMIT-BIH database consists of various ECG signals involving a patient and standard ECG signals.MATLAB can be considered as the simulation tool used in this work.The proposed method’s uniqueness was inspired by the compression ratio(CR)and achieved by MDCT.The performance measurement of the recovered signal was done by calculating the percentage root mean difference(PRD),mean square error(MSE),and peak signal to noise ratio(PSNR)besides the calculation of CR.Finally,the simulation results indicated that this work is one of the most important works in ECG signal compression.

关键词： Compressive sensing sparse beats of hearts compression ratio percentage root mean difference

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Synergistic impacts of rifampicin and doxorubicin against thioacetamide-induced hepatocellular carcinoma in rats

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Liver Research 2023年第4期7卷 352-360页

作者： zahraa R.Elshahawy Entsar A.Saad Rana R.El-Sadda Chemistry Department Faculty of ScienceDamietta UniversityDamiettaEgypt Gastroenterology Surgical Center Faculty of MedicineMansoura UniversityMansouraEgypt

Background and aims:Combination therapy is a promising new strategy that has been proposed to increase the efficacy of cancer treatment.We aimed to investigate the anti-cancer activity of rifampicin monotherapy and its combination with doxorubicin against hepatocellular carcinoma(HCC).Materials and methods:The in vitro half maximal inhibitory concentration(IC50)and selectivity index(SI)of the drugs under investigation against HepG2 and human lung fibroblast(WI38)cell lines were determined.For the in vivo experiment,male Sprague-Dawley albino rats were injected with thioacetamide at 200 mg/kg twice a week for 90 days;HCC development was confirmed histopathologically.Following HCC induction,the rats were treated with intraperitoneal doxorubicin,rifampicin,or their combination for 45 or 90 days.After sacrifice,the livers were examined histopathologically.The levels of aminotransferases,albumin,bilirubin,malondialdehyde,superoxide dismutase(SOD),catalase(CAT),total antioxidant capacity(TAC),and nitric oxide were measured by spectrophotometry.Alphafetoprotein,cancer antigen 19-9,tumor necrosis factor-alpha,interleukin-6,Bcl-2-associated X protein,caspase 3,caspase 8,and p53 were estimated using ELISA.Results:In vitro,the combination of doxorubicin and rifampicin showed the highest SI of 3.43.In vivo,among the measured markers,the levels of TAC,CAT,SOD,and p53 decreased(P<0.001)and the rest of the measured marker levels increased(P<0.001)in the HCC-bearing rats;after treatment in all groups,all these changes improved toward normal in a time-dependent manner.The combination of doxorubicin and rifampicin optimized the effects of the two individual drugs and exerted the best antioxidant effects.Conclusions:In general,compared with rifampicin or doxorubicin alone,combination therapy has favorable outcomes.Based on our results,the combination of rifampicin and doxorubicin might be applicable for HCC chemotherapy.

关键词： Hepatocellular carcinoma(HCC) Rifampicin Doxorubicin Bcl-2-associated X protein(Bax) Caspase Protein 53(p53) Thioacetamide

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Extracellular vesicles and reproduction-promotion of successful pregnancy

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Cellular & Molecular Immunology 2014年第6期11卷 548-563页

作者： Dionne TannettaI Rebecca Dragovic zahraa Alyahyaei Jennifer Southcombe Nuffield Department of Obstetrics and Gynaecology University of Oxford John Radcliffe Hospital Oxford UK

Extracellular vesicles （EVs） are membrane-bound complexes secreted from cells under both physiological and pathological conditions. They contain proteins, nucleic acids and lipids and act as messengers for cell-cell communication and signalling, particularly between immune cells. EV research is a rapidly evolving and expanding field, and it appears that all biological fluids contain very large numbers of EVs; they are produced from all cells that have been studied to date, and are known to have roles in several reproductive processes. This review analyses the evidence for the role of EVs throughout human reproduction, starting with the paternal and maternal gametes, followed by the establishment and continuation of successful pregnancies, with specific focus, where possible, on the interaction of EVs with the maternal immune system. Importantly, variations within the EV populations are identified in various reproductive disorders, such as pre-term labour and pre-eclampsia.

关键词： Extracellular vesicles pregnancy microvesicles exosomes nanoparticle tracking analysis pre-eclampsia

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Multi-Mode Frequency Reconfigurable Conformal Antenna for Modern Electronic Systems

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Computers, Materials & Continua 2022年第11期73卷 3861-3877页

作者： Abir Zaidi Esraa Mousa Ali Abdullah G.Alharbi Salah Ud-Din Khan Mohammad Alsharef Mohammed S.alzaidi Sherif S.M.Ghoneim Laboratory EEA&TI Faculty of Science and Techniques(FSTM)MohammediaHassan II UniversityCasablancaMorocco Faculty of Aviation Sciences Amman Arab UniversityAmman11953Jordan Department of Electrical Engineering Faculty of EngineeringJouf UniversitySakaka42421Saudi Arabia Sustainable Energy Technologies Center College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudia Arabia Electrical Engineering Department College of EngineeringTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

The article presents a miniaturized monopole antenna dedicated to modern flexible electronic systems.The antenna combines three fundamental properties in a single structure.Firstly,it is characterized by a compact size compared to the state-of-the-art literature with an overall size of 18×18×0.254 mm3,secondly,the proposed antenna integrates the reconfigurability function of frequency,produced by means of a Positive-IntrinsicNegative(PIN)diode introduced into the radiating element.Thus,the antenna is able to switch between different frequencies and different modes,making it suitable to meet the ever-changing demands of communication systems.third,the antenna is equipped by the property of flexibility.In fact,a conformability test is performed and has demonstrated the stability of the antenna performance under normal and bending conditions.Finally,in order to demonstrate the potential of the proposed antenna,a comparison between the simulated and measured results is made and turned out to be a strong agreement,making the antenna an excellent candidate for future miniaturized rigid and conformal devices.

关键词： Monopole antenna frequency reconfigurable co-planar waveguide(CPW)fed flexible electronics compact size

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Chaotic Flower Pollination with Deep Learning Based COVID-19 Classification Model

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Computers, Materials & Continua 2023年第3期74卷 6195-6212页

作者： T.Gopalakrishnan Mohamed Yacin Sikkandar Raed Abdullah Alharbi P.Selvaraj zahraa H.Kareem Ahmed Alkhayyat Ali Hashim Abbas Department of Information Technology Manipal Institute of Technology BengaluruManipal Academy of Higher EducationManipalIndia Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Public Health Department College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Department of Computing Technologies College of Engineering and TechnologyFaculty of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203TamilnaduIndia Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University CollegeBabylonIraq College of Technical Engineering The Islamic UniversityNajafIraq College of Information Technology Imam Ja’afar Al-Sadiq UniversityAl-Muthanna66002Iraq

The Coronavirus Disease(COVID-19)pandemic has exposed the vulnerabilities of medical services across the globe,especially in underdeveloped nations.In the aftermath of the COVID-19 outbreak,a strong demand exists for developing novel computer-assisted diagnostic tools to execute rapid and cost-effective screenings in locations where many screenings cannot be executed using conventional methods.Medical imaging has become a crucial component in the disease diagnosis process,whereas X-rays and Computed Tomography(CT)scan imaging are employed in a deep network to diagnose the diseases.In general,four steps are followed in image-based diagnostics and disease classification processes by making use of the neural networks,such as network training,feature extraction,model performance testing and optimal feature selection.The current research article devises a Chaotic Flower Pollination Algorithm with a Deep Learning-Driven Fusion(CFPADLDF)approach for detecting and classifying COVID-19.The presented CFPA-DLDF model is developed by integrating two DL models to recognize COVID-19 in medical images.Initially,the proposed CFPA-DLDF technique employs the Gabor Filtering(GF)approach to pre-process the input images.In addition,a weighted voting-based ensemble model is employed for feature extraction,in which both VGG-19 and the MixNet models are included.Finally,the CFPA with Recurrent Neural Network(RNN)model is utilized for classification,showing the work’s novelty.A comparative analysis was conducted to demonstrate the enhanced performance of the proposed CFPADLDF model,and the results established the supremacy of the proposed CFPA-DLDF model over recent approaches.

关键词： Deep learning medical imaging fusion model chaotic models ensemble model COVID-19 detection

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Eye Detection-Based Deep Belief Neural Networks and Speeded-Up Robust Feature Algorithm

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Computer Systems Science & Engineering 2023年第6期45卷 3195-3213页

作者： zahraa Tarek Samaa M.Shohieb Abdelghafar M.Elhady El-Sayed M.El-kenawy Mahmoud Y.Shams Faculty of Computers and Information Mansoura UniversityMansoura35516Egypt Deanship of Scientific Research Umm Al-Qura UniversityMakkah21955KSA Delta Higher Institute of Engineering and Technology Mansoura35111Egypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The ability to detect and localize the human eye is critical for use in security applications and human identification and verification systems.This is because eye recognition algorithms have multiple challenges,such as multi-pose variations,ocular parts,and illumination.Moreover,the modern security applica-tions fail to detect facial expressions from eye images.In this paper,a Speeded-Up Roust Feature(SURF)Algorithm was utilized to localize the face images of the enrolled subjects.We highlighted on eye and pupil parts to be detected based on SURF,Hough Circle Transform(HCT),and Local Binary Pattern(LBP).Afterward,Deep Belief Neural Networks(DBNN)were used to classify the input features results from the SURF algorithm.We further determined the correctly and wrongly classified subjects using a confusion matrix with two class labels to classify people whose eye images are correctly detected.We apply Stochastic Gradient Descent(SGD)optimizer to address the overfitting problem,and the hyper-parameters arefine-tuned based on the applied DBNN.The accuracy of the proposed system is determined based on SURF,LBP,and DBNN classifier achieved 95.54%for the ORL dataset,94.07%for the BioID,and 96.20%for the CASIA-V5 dataset.The proposed approach is more reliable and more advanced when compared with state-of-the-art algorithms.

关键词： Eye localization classification DBNN detection feature extraction LBP feature extraction SURF

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